from matplotlib import pyplot as plt

data = [
    35.1572,
    35.127,
    35.2324,
    35.2354,
    35.0273,
    35.1826,
    34.9893,
    38.5166,
    26.0977,
    19.8721,
    16.7422,
    15.1475,
    15.3086,
    15.2256,
    15.3184,
    15.3652,
    17.7168,
    21.9326,
    31.0332,
    33.0059,
    32.7275,
    28.2588,
    28.2734,
    40.2373,
    40.2959,
    40.2861,
    40.2666,
    40.3613,
    40.3311,
    40.4531,
    40.3613,
    35.7764,
    27.9834,
    27.8662,
    27.9258,
    28.0811,
    28.1807,
    27.9951,
    37.1006,
    23.1748,
    18.5166,
    16.0391,
    15.2021,
    15.1699,
    15.1309,
    15.1172,
    15.1289,
    15.7246,
    18.8232,
    23.3682,
    37.2588,
    30.6934,
    28.5869,
    29.7734,
    39.3359,
]

data_mean = [
    35.1572,
    35.1526,
    35.1649,
    35.1757,
    35.1529,
    35.1575,
    35.1316,
    35.6524,
    34.1824,
    31.9808,
    29.6364,
    27.4073,
    25.546,
    23.9582,
    22.629,
    21.5115,
    20.9277,
    21.0823,
    22.6132,
    24.2121,
    25.5222,
    25.9432,
    26.3017,
    28.4456,
    30.2687,
    31.8099,
    33.1109,
    34.2264,
    35.1655,
    35.979,
    36.6532,
    36.5183,
    35.2053,
    34.0762,
    33.13,
    32.3532,
    31.7113,
    31.1396,
    32.0566,
    30.6902,
    28.8173,
    26.8514,
    25.0592,
    23.5378,
    22.2444,
    21.1479,
    20.2219,
    19.53,
    19.4213,
    20.0285,
    22.6793,
    23.9123,
    24.6314,
    25.4225,
    27.563,
]

outliers = [
    7,
    8,
    23,
    31,
    32,
    38,
    50
]

plt.plot(data)
plt.plot(data_mean)
[plt.axvline(x = outlier, color = 'red') for outlier in outliers]
plt.show()